Demonstrations of RADARSAT-1 Sample Functions

This Jupyter Notebook contains sample outputs for many of the functions in the GitHub repo, as well as brief demonstrations of how the results can be used.

get_metadata.py

This file contains several functions for downloading metadata for images without downloading the image itself. Data is then returned as a Pandas DataFrame and can also be output as a CSV if desired.

Running the Scripts

Uses for the scripts

The metadata for the images has a variety of uses, such as allowing to find imagery by date, by location, or even by the sensor mode from the satellite. Since the data is returned as a Dataframe, there's a wide variety of analysis possible.

Some sample code using the metadata can be found in the sample_algorithms.py file as well.

Finding amount of imagery per month

downloading_files.py

This file contains several functions for downloading images. Images are downloaded in a GeoTIFF format, which allows them to be viewed in QGIS or other geospatial tools. Note: These files can be large, normally ranging from 150 - 600 MB. Make sure you have storage space appropriate for them. It can also take a long time to download them, especially if a large number of images is being downloaded.

Running the scripts

Files downloaded by these scripts will be placed into folders by year / month. For example, all files from August 2009 will be placed into a 2009/8/ directory.

sample_algorithms.py

This file contains several functions to showcase possible tasks performed with R-1 imagery or metadata.

Running the scripts

create_a_map(start_year, start_month, end_year, end_month)

This script will create a map showing the location of imagery during a given period.

borders(img_url)

This is a very basic script that attempts to find the borders between land and water for a given image.

chart_imagery_by_date(start_year, start_month, end_year, end_month)

This function plots how much imagery was taken per month for a given period